SimonBlanke /
Hyperactive
| @@ 284-316 (lines=33) @@ | ||
| 281 | assert d_time_frac > 1.5 |
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| 282 | ||
| 283 | ||
| 284 | @pytest.mark.parametrize("search_space", search_space_list) |
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| 285 | def test_memory_warm_start_1(search_space): |
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| 286 | n_iter = 1500 |
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| 287 | ||
| 288 | c_time = time.perf_counter() |
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| 289 | hyper0 = Hyperactive(distribution="pathos") |
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| 290 | hyper0.add_search( |
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| 291 | objective_function, search_space, n_iter=n_iter, n_jobs=2, memory=True |
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| 292 | ) |
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| 293 | hyper0.run() |
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| 294 | d_time_1 = time.perf_counter() - c_time |
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| 295 | ||
| 296 | search_data0 = hyper0.search_data(objective_function) |
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| 297 | ||
| 298 | c_time = time.perf_counter() |
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| 299 | hyper1 = Hyperactive(distribution="pathos") |
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| 300 | hyper1.add_search( |
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| 301 | objective_function, |
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| 302 | search_space, |
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| 303 | n_iter=n_iter, |
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| 304 | n_jobs=2, |
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| 305 | memory=True, |
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| 306 | memory_warm_start=search_data0, |
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| 307 | ) |
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| 308 | hyper1.run() |
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| 309 | d_time_2 = time.perf_counter() - c_time |
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| 310 | ||
| 311 | d_time_frac = d_time_1 / d_time_2 |
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| 312 | ||
| 313 | print("\n d_time_1 ", d_time_1) |
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| 314 | print("\n d_time_2 ", d_time_2) |
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| 315 | ||
| 316 | assert d_time_frac > 1.5 |
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| 317 | ||
| @@ 217-248 (lines=32) @@ | ||
| 214 | return 0 |
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| 215 | ||
| 216 | ||
| 217 | @pytest.mark.parametrize("search_space", search_space_list) |
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| 218 | def test_memory_warm_start_0(search_space): |
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| 219 | n_iter = 1500 |
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| 220 | ||
| 221 | c_time = time.perf_counter() |
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| 222 | hyper0 = Hyperactive(distribution="pathos") |
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| 223 | hyper0.add_search( |
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| 224 | objective_function, search_space, n_iter=n_iter, n_jobs=2, memory=True |
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| 225 | ) |
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| 226 | hyper0.run() |
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| 227 | d_time_1 = time.perf_counter() - c_time |
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| 228 | ||
| 229 | search_data0 = hyper0.search_data(objective_function) |
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| 230 | ||
| 231 | c_time = time.perf_counter() |
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| 232 | hyper1 = Hyperactive() |
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| 233 | hyper1.add_search( |
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| 234 | objective_function, |
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| 235 | search_space, |
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| 236 | n_iter=n_iter, |
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| 237 | memory_warm_start=search_data0, |
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| 238 | memory=True, |
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| 239 | ) |
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| 240 | hyper1.run() |
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| 241 | d_time_2 = time.perf_counter() - c_time |
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| 242 | ||
| 243 | d_time_frac = d_time_1 / d_time_2 |
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| 244 | ||
| 245 | print("\n d_time_1 ", d_time_1) |
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| 246 | print("\n d_time_2 ", d_time_2) |
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| 247 | ||
| 248 | assert d_time_frac > 1.5 |
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| 249 | ||
| 250 | ||
| 251 | @pytest.mark.parametrize("search_space", search_space_list) |
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| @@ 251-281 (lines=31) @@ | ||
| 248 | assert d_time_frac > 1.5 |
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| 249 | ||
| 250 | ||
| 251 | @pytest.mark.parametrize("search_space", search_space_list) |
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| 252 | def test_memory_warm_start_1(search_space): |
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| 253 | n_iter = 1500 |
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| 254 | ||
| 255 | c_time = time.perf_counter() |
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| 256 | hyper0 = Hyperactive() |
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| 257 | hyper0.add_search(objective_function, search_space, n_iter=n_iter, memory=True) |
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| 258 | hyper0.run() |
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| 259 | d_time_1 = time.perf_counter() - c_time |
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| 260 | ||
| 261 | search_data0 = hyper0.search_data(objective_function) |
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| 262 | ||
| 263 | c_time = time.perf_counter() |
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| 264 | hyper1 = Hyperactive(distribution="pathos") |
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| 265 | hyper1.add_search( |
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| 266 | objective_function, |
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| 267 | search_space, |
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| 268 | n_iter=n_iter, |
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| 269 | n_jobs=2, |
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| 270 | memory=True, |
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| 271 | memory_warm_start=search_data0, |
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| 272 | ) |
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| 273 | hyper1.run() |
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| 274 | d_time_2 = time.perf_counter() - c_time |
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| 275 | ||
| 276 | d_time_frac = d_time_1 / d_time_2 |
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| 277 | ||
| 278 | print("\n d_time_1 ", d_time_1) |
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| 279 | print("\n d_time_2 ", d_time_2) |
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| 280 | ||
| 281 | assert d_time_frac > 1.5 |
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| 282 | ||
| 283 | ||
| 284 | @pytest.mark.parametrize("search_space", search_space_list) |
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| @@ 313-343 (lines=31) @@ | ||
| 310 | """ |
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| 311 | ||
| 312 | ||
| 313 | @pytest.mark.parametrize("search_space", search_space_list) |
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| 314 | def test_memory_warm_start_1(search_space): |
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| 315 | n_iter = 1500 |
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| 316 | ||
| 317 | c_time = time.perf_counter() |
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| 318 | hyper0 = Hyperactive() |
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| 319 | hyper0.add_search(objective_function, search_space, n_iter=n_iter, memory=True) |
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| 320 | hyper0.run() |
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| 321 | d_time_1 = time.perf_counter() - c_time |
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| 322 | ||
| 323 | search_data0 = hyper0.search_data(objective_function) |
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| 324 | ||
| 325 | c_time = time.perf_counter() |
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| 326 | hyper1 = Hyperactive(distribution="joblib") |
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| 327 | hyper1.add_search( |
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| 328 | objective_function, |
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| 329 | search_space, |
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| 330 | n_iter=n_iter, |
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| 331 | n_jobs=1, |
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| 332 | memory=True, |
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| 333 | memory_warm_start=search_data0, |
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| 334 | ) |
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| 335 | hyper1.run() |
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| 336 | d_time_2 = time.perf_counter() - c_time |
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| 337 | ||
| 338 | d_time_frac = d_time_1 / d_time_2 |
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| 339 | ||
| 340 | print("\n d_time_1 ", d_time_1) |
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| 341 | print("\n d_time_2 ", d_time_2) |
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| 342 | ||
| 343 | assert d_time_frac > 1.5 |
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| 344 | ||
| 345 | ||
| 346 | """ |
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